Transformers documentation
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Tutorials
Pipelines for inferenceLoad pretrained instances with an AutoClassPreprocessFine-tune a pretrained modelDistributed training with 🤗 AccelerateShare a model
How-to guides
General usage
Create a custom architectureSharing custom modelsTrain with a scriptRun training on Amazon SageMakerConverting from TensorFlow checkpointsExport to ONNXExport to TorchScriptTroubleshoot
Natural Language Processing
Audio
Computer Vision
Performance and scalability
OverviewTraining on one GPUTraining on many GPUsTraining on CPUTraining on many CPUsTraining on TPUsTraining on Specialized HardwareInference on CPUInference on one GPUInference on many GPUsInference on Specialized HardwareCustom hardware for trainingInstantiating a big modelDebuggingHyperparameter Search using Trainer API
Contribute
How to contribute to transformers?How to add a model to 🤗 Transformers?How to convert a 🤗 Transformers model to TensorFlow?How to add a pipeline to 🤗 Transformers?TestingChecks on a Pull Request
🤗 Transformers NotebooksCommunity resourcesBenchmarksMigrating from previous packagesConceptual guides
PhilosophyGlossarySummary of the tasksSummary of the modelsSummary of the tokenizersPadding and truncationBERTologyPerplexity of fixed-length models
API
Main Classes
Auto ClassesCallbacksConfigurationData CollatorKeras callbacksLoggingModelsText GenerationONNXOptimizationModel outputsPipelinesProcessorsTokenizerTrainerDeepSpeed IntegrationFeature ExtractorImage Processor
Models
Text models
Vision models
Audio models
Multimodal models
Reinforcement learning models
Time series models
Internal Helpers
You are viewing v4.25.1 version. A newer version v5.8.1 is available.
Run training on Amazon SageMaker
The documentation has been moved to hf.co/docs/sagemaker. This page will be removed in transformers 5.0.